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Bioinformatics. 2014 Sep 15;30(18):2676-7. doi: 10.1093/bioinformatics/btu362. Epub 2014 May 28.

CODOC: efficient access, analysis and compression of depth of coverage signals.

Author information

1
Center for Integrative Bioinformatics Vienna (CIBIV), Max F Perutz Laboratories, University of Vienna and Medical University of Vienna, Dr. Bohrgasse 9, 1030 Vienna, Austria.

Abstract

Current data formats for the representation of depth of coverage data (DOC), a central resource for interpreting, filtering or detecting novel features in high-throughput sequencing datasets, were primarily designed for visualization purposes. This limits their applicability in stand-alone analyses of these data, mainly owing to inaccurate representation or mediocre data compression. CODOC is a novel data format and comprehensive application programming interface for efficient representation, access and analysis of DOC data. CODOC compresses these data ∼ 4-32× better than the best current comparable method by exploiting specific data characteristics while at the same time enabling more-exact signal recovery for lossy compression and very fast query answering times.

AVAILABILITY AND IMPLEMENTATION:

Java source code and binaries are freely available for non-commercial use at http://purl.org/bgraph/codoc.

PMID:
24872424
DOI:
10.1093/bioinformatics/btu362
[Indexed for MEDLINE]

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